Senior Technical Architect

InterSystems•Boston, MA

14h

About The Position

We are seeking an experienced Technical Architect to serve as the technical leader of our Supply Chain Data development team. This role will own architectural vision, technical standards, and solution design across our supply chain solutions built on top of our core enterprise data platform. The Technical Architect will bridge technology and business, lead adoption of emerging technologies (including GenAI), mentor engineers across all aspects of software development, and act as a trusted technical advisor to both internal stakeholders and customers. This is a technical leadership role requiring deep technical expertise, strong business acumen, and the ability to influence across engineering, product, sales, and executive teams.

Requirements

10+ years of experience in software engineering, with at least 5 years in architecture or technical leadership roles.
Strong experience designing and delivering enterprise-grade data platforms or distributed systems.
Deep knowledge of:
Data architecture (data modeling, integration, ETL/ELT, streaming)
APIs and microservices architecture
Cloud platforms (Azure, AWS, or GCP)
CI/CD, DevOps, and containerization (Docker, Kubernetes)
Experience with AI/ML integration; exposure to Generative AI, LLMs, or intelligent automation preferred.
Strong understanding of non-functional requirements: scalability, performance, security, observability, resiliency.
Experience working directly with customers in technical advisory or solution architecture roles.
Proven track record of mentoring engineers and raising overall engineering quality.
Strategic thinker with hands-on technical depth.
Strong decision-maker who balances pragmatism and innovation.
Ability to influence without authority.
Comfortable operating in ambiguity and scaling teams and architecture.
Passion for mentoring and building high-performing engineering teams.
Business-oriented mindset with the ability to connect architecture decisions to ROI.

Nice To Haves

Experience in supply chain domain (planning, inventory, logistics, demand forecasting, procurement, etc.).
Experience building on top of a core enterprise data platform or data fabric architecture.
Experience with:
Decision intelligence solutions
Real-time data processing
Vector databases and AI integration patterns
Low-code or composable platform architectures
Familiarity with data governance, data quality, and master data management.
Strong communication and presentation skills with executive-level stakeholders.

Responsibilities

Define and own the overall architecture strategy for supply chain products and solutions.
Establish and enforce architectural principles, design standards, and engineering best practices.
Lead solution design for complex data integration, analytics, AI, and application use cases.
Ensure scalability, performance, reliability, security, and maintainability (functional and non-functional requirements).
Drive modernization initiatives including cloud-native architectures, microservices, APIs, and data-driven solutions.
Evaluate and lead adoption of new technologies, including Generative AI, data fabric architectures, and intelligent automation.
Identify high-value use cases for GenAI and AI within supply chain workflows.
Define architecture patterns for integrating LLMs, vector search, and AI services into enterprise systems.
Establish governance, security, and responsible AI practices.
Work with product and business stakeholders to translate AI innovation into measurable business outcomes.
Act as subject matter expert (SME) in customer interactions, architecture discussions, and solution workshops.
Translate complex technical concepts into clear business value propositions.
Support pre-sales activities, PoCs, and strategic customer initiatives.
Provide best practices guidance on supply chain data management, integration, analytics, and system design.
Mentor junior and mid-level engineers across:
Architecture and system design
Coding standards and code reviews
DevOps and CI/CD
Testing strategies
Operational readiness and supportability
Promote engineering discipline across the full software lifecycle (design → development → testing → deployment → maintenance → support).
Foster a culture of technical ownership, continuous learning, and innovation.
Serve as technical advisor to product management and management team.
Contribute to product roadmap discussions from an architectural and technical feasibility perspective.
Identify long-term technology trends relevant to supply chain and data platforms.
Help align engineering investments with company strategy.